About this role
This role suits an experienced quantitative professional with financial services expertise who wants to lead machine learning initiatives for new financial products in the United States. The Staff Data Scientist position at Zip Co Limited is a remote-first opportunity with an option to work from the Manhattan office.
Role Overview
Zip Co Limited is seeking a Staff Data Scientist to own analytical strategy and build foundational machine learning and artificial intelligence solutions. This greenfield opportunity involves designing new models using bank transaction data to support financial products like cash advances and rent advances. The position requires mentoring junior team members, experimenting independently, and collaborating with engineering teams to productionize scalable solutions.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
Salary and Benefits
About the Company
Zip Co Limited is a digital financial services company offering innovative, people-centered products including point-of-sale credit and digital payment services. Operating across Australia, New Zealand, and the United States, the organization connects millions of customers with a global network of tens of thousands of merchants.
How to Apply
Interested candidates should apply directly on the official company careers page.
Skills and tech stack
Questions candidates ask
Is this position remote?
Yes, this is a remote-first opportunity for United States-based employees, with an optional workspace available in the Manhattan office.
What is the salary range for the Staff Data Scientist role?
The annual base pay range is $192,000 to $240,000, determined by individual factors such as knowledge, skills, experience, and location.
What level of experience is required?
Candidates must have at least 7 years of experience in data science, including 4 years specifically in financial services.
Is visa sponsorship available?
No, visa sponsorship is not available for this position.
What technical skills are needed?
Proficiency in Python and SQL is required, alongside experience with neural networks, large language models, generative AI, and cashflow data.